Tailin Liang
Impact in
- Computational Mathematics top 10%
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- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
Papers in
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- Advanced Neural Network Applications 3
-
- Wireless Signal Modulation Classification 1
- Computational Physics and Python Applications 1
- Domain Adaptation and Few-Shot Learning 1
- Co-authors
- John Glossner (4 shared papers)Lei Wang (2 shared papers)Wei Huang (1 shared paper)Mayan Moudgill (1 shared paper)Xiaodong Zhang (1 shared paper)
- Journals
- ACM Transactions on Embedded Computing Systems (1 paper)Neurocomputing (1 paper)2022 Design, Automation & Test in Europe Conference & Exhibition (DATE) (1 paper)
- Partner nations
- China
In The Last Decade
Tailin Liang
2 papers receiving 521 citations
Tailin Liang's Hit Papers
Peers
Comparison fields: 5 of 87
- Computational Mathematics 9
- Computer Vision and Pattern Recognition 251
- Artificial Intelligence 242
- Hardware and Architecture 35
- Signal Processing 41
Countries citing papers authored by Tailin Liang
This map shows the geographic impact of Tailin Liang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tailin Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tailin Liang more than expected).
Fields of papers citing papers by Tailin Liang
This network shows the impact of papers produced by Tailin Liang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tailin Liang. The network helps show where Tailin Liang may publish in the future.
Co-authors
The 5 scholars most cited alongside Tailin Liang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Pruning and quantization for deep neural network acceleration: A survey Hit paper breakdown → | 2021 | 538 |
| 2 | 2020 | 4 | |
| 3 | 2022 | 1 | |
| 4 | 2022 | 0 |
About Tailin Liang
Tailin Liang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mathematics, Hardware and Architecture and Computational Mechanics, having authored 4 papers that have together received 543 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (3 papers), Tensor decomposition and applications (2 papers), Parallel Computing and Optimization Techniques (2 papers), Wireless Signal Modulation Classification (1 paper), Sparse and Compressive Sensing Techniques (1 paper), Advanced Memory and Neural Computing (1 paper), Computational Physics and Python Applications (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Computational Mathematics (9 citations), Computer Vision and Pattern Recognition (251 citations), Artificial Intelligence (242 citations), Hardware and Architecture (35 citations) and Signal Processing (41 citations). Tailin Liang has collaborated with scholars based in China. Frequent co-authors include John Glossner, Lei Wang, Wei Huang, Mayan Moudgill and Xiaodong Zhang. Their work appears in journals such as ACM Transactions on Embedded Computing Systems, Neurocomputing and 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.